David Knott 08/10/2026 David Knott 08/10/2026

Thanks for the panic: can we turn that energy into something useful now?

There have been a lot of big things to worry about related to AI recently: mass loss of jobs, hacking attacks, rogue agents, stock market bubbles, existential threats to humanity, machines with souls, online torture chambers and so on. This worry has been amplified by the weird see-saw positions from AI companies, which go something like: ‘Everything’s going to be great! Unless it’s terrible. Unless it’s great! Unless it’s terrible.’

Panic may seem an appropriate response to such alarming prospects, contradiction and confusion, especially when it feels like there is little that you can do about them personally. Can you use Copilot to compose an email in a way that avoids intellectual decay and environmental catastrophe? Does adding ‘please’ at the end of your prompts (or avoiding doing so) express a position about whether models have rights and consciousness? When you write code that calls an LLM API, are you surrendering or protecting your organisation’s independence and sovereignty? Meaningful engagement feels out of our reach; panic, frustration and the sense of being overwhelmed are always at hand.

David Knott 12/11/2025 David Knott 12/11/2025

There’s plenty of room on the LILO

What are LLMs good for? Everything, if you believe marketing announcements and press releases. Very little, if you believe the most sceptical of sceptics. It sometimes seems that we are still waiting for the crowning innovation, the killer app that will secure the place of LLMs in our enterprise – or the deflating moment when we realise that our expectations cannot be met.

While we are waiting for that moment, I think there is plenty for us to do by putting LLMs to work in relatively mundane contexts. What are they good for? There’s a clue in the name: Large Language Models are good at language, something which traditional computing has been notoriously bad at for most of its existence.

David Knott 08/10/2025 David Knott 08/10/2025

Three sentences that I say too often - and will keep on saying

The longer I spend in leadership roles, the more often I find myself saying the same things over and over again. I expect that part of this is due to intellectual laziness – it’s easier to recycle the same thoughts than to have new thoughts. But part of it is because, over the years, I have found leadership principles that work for me, and words which express them concisely.

There are three things in particular which I say a lot, which my team sometimes tells me that I say too much. None of them are original – they are all ideas which I have learnt from others. They are . . .

David Knott 12/12/2024 David Knott 12/12/2024

Precision is not pedantry; clarity is not cynicism

The Nomenclature Committee of the Association of Computing Machinery might not sound very exciting. However, it got to decide the words that we use to describe computers, and words matter: naming is a powerful act. When the computing pioneer, Grace Hopper, chaired the committee in the 1950s, she steered them to avoid ‘words of the magic brain class’, and to use terms such as ‘storage’ instead of ‘memory’, and ‘processing’ instead of ‘thinking’.

This direction was needed in the 1950s. Computers were new, and to most people they seemed like magic. Even though the computation they performed was complex - since the early days, computers had been used for hard mathematical problems such as code breaking and navigation - they did far less than the computers we have today. Today, it would seem strange to describe a machine that was limited to mathematical operations (no speech, no graphics, no sound) as thinking. Yet, in those early days, it was astonishing that computers could compute at all: that they could do work previously reserved for the human brain and mind. It is unsurprising that they were described with breathless excitement.

David Knott 02/11/2023 David Knott 02/11/2023

The vicious circle of legacy technology

Where does a vicious circle start?

I think that, in the case of legacy technology, it starts with an implicit agreement: to optimise for short-term outcomes over sustained capability. I also think that, once that implicit agreement gets the vicious circle of legacy technology going, it gets progressively more difficult to stop.

Let’s take a step back, and make it clear what we mean by legacy technology, and what it means to optimise for short-term outcomes.

‘Legacy’ is a euphemism. In normal language, it means something good: the things that we are proud to leave behind. In enterprise technology, it means something bad: the systems that have truly been left behind, in the sense that technology, capability and best practice have all moved on.